Arabic AI Data Infrastructure
Arabic speech data built for real-world AI.
Collect, annotate, and evaluate Arabic speech data across MENA — with verified native speakers, dialect-level targeting, and enterprise-grade quality control.
Conversational Saudi Arabic for a voice agent
- Dialect
- Najdi · Hijazi
- Speech
- Spontaneous, two-speaker calls
- Speakers
- Verified native · balanced gender · 18–60
- Conditions
- Mobile · quiet & noisy
- Annotation
- Verbatim transcript · diarization · timestamps
- Delivery
- WAV + JSON manifest, consent records
One accountable partner for the full Arabic speech data lifecycle — for teams building ASR, TTS, voice agents, and contact-center AI.
- Collect
- Annotate
- Evaluate
- Improve
The problem
Arabic isn’t one language to your model.
Models that do well on Modern Standard Arabic often struggle with the way people actually speak.
Dialects
Najdi and Egyptian differ in vocabulary, grammar, and sound — data from one doesn’t transfer to the other.
Code-switching
Arabic–English mixing mid-sentence is everyday speech across the Gulf, not an edge case.
Real conditions
Car cabins, call centers, and busy streets sound nothing like a studio.
Speakers
Age, gender, region, and speaking style all shift how a model hears Arabic.
What we do
Collect. Annotate. Evaluate.
Three services, one managed workflow. Use one, or run the full cycle with us.
Custom Arabic speech data
Tell us the speech your model needs. We recruit the speakers, record it, and deliver it validated.
- Dialect, region, and demographic targeting
- Scripted, prompted, or spontaneous speech
- Consent and usage rights documented
Arabic-native speech annotation
Bring your own audio. Native-speaker annotators transcribe and label it to your specification.
- Transcription, timestamps, and diarization
- Dialect, intent, and entity labels
- Code-switching identified, not ignored
Arabic voice AI evaluation
Measure how your ASR or voice agent performs on each dialect and real-world condition — before your users do.
- Dialect-level test sets
- Clean, noisy, and code-switched conditions
- Weaknesses mapped to the data that fixes them
Dialect-level targeting
Arabic isn’t one dataset.
Specify the dialects and speaker profiles your model needs — down to the region. We build the dataset around them.
“500 hours of conversational Saudi Arabic from verified Najdi speakers.”
“Evaluate our voice agent across Najdi, Hijazi, Egyptian, and Jordanian Arabic.”
Saudi Arabia
- Najdi
- Hijazi
- Eastern
- Southern
Gulf
- Emirati
- Kuwaiti
- Qatari
- Bahraini
- Omani
Levant
- Jordanian
- Palestinian
- Lebanese
- Syrian
Egypt
- Egyptian
Iraq
- Iraqi
North Africa / Maghreb
- Moroccan
- Algerian
- Tunisian
How it works
A managed workflow, start to finish.
You define what the model needs. We run everything behind it.
-
01
Tell us what your model needs
Dialects, speakers, recording conditions, hours, annotation, and acceptance criteria.
-
02
We design the project
Collection methodology, speaker requirements, QA rules, and delivery spec.
-
03
We collect and annotate
Verified speakers and trained annotators work inside our managed workflow.
-
04
Multi-stage QA
Audio, transcripts, dialect, and metadata are checked against your requirements.
-
05
Receive AI-ready data
Structured files and documentation, in the format you agreed.
-
06
Scale
Once the pilot passes, expand across speakers, dialects, and environments.
Quality assurance
Quality before quantity.
Every project has written acceptance criteria. Data that doesn’t meet them isn’t delivered — it’s re-recorded or re-annotated.
Checks are set per project and can include:
- Audio quality silence, clipping, background noise
- Duplicates repeated or reused recordings
- Language & dialect the right speech, from the right speaker
- Transcripts accuracy against your guidelines
- Metadata speaker and session fields complete
- Human review a separate reviewer approves or sends back
Use cases
Built for teams shipping Arabic voice AI.
Voice agents
Train agents to understand how customers actually speak.
Speech recognition
Improve ASR across dialects, accents, and noisy environments.
Contact centers
Build and evaluate models on real conversational patterns.
Automotive voice
Speech across dialects and in-cabin acoustic conditions.
Healthcare voice
Domain-specific Arabic speech under controlled requirements.
Arabic–English code-switching
Natural bilingual speech, as it’s spoken across MENA.
Enterprise security
Your data stays under control.
Speech data is personal. Every project runs with defined access, consent, and usage rights.
- Controlled access only assigned team members reach project data
- Confidentiality NDAs and project agreements before work starts
- Participant consent every speaker consents to the specific use
- Defined usage rights commercial rights set out in your agreement
- Retention data kept and deleted as your agreement specifies
- Hosting requirements regional or in-environment delivery discussed at scoping
Start small
Start with a focused pilot.
Need Saudi Arabic data? Begin with a small, representative dataset, check it against your model, then scale with confidence.
- Define requirements
- Collect a sample
- Validate quality
- Approve
- Scale
Request a pilot
Tell us what your model needs to hear.
Share your use case, dialects, and volume. We’ll come back with a pilot scope, timeline, and quote.
Prefer email? [email protected]
Request received
Thank you — we’ll review your requirements and follow up to scope a pilot. A confirmation is on its way to your inbox.